Target identification method and device based on double-flow symmetric feature fusion network model

The embodiment of the invention discloses a target identification method and device based on a double-flow symmetric feature fusion network model. The method comprises the following steps: inputting a visible light image and an infrared image into a double-flow symmetric feature fusion network in which an attention mechanism is introduced to extract features so as to obtain visible light image features and infrared image features; calling an identification model according to the visible light image features and the infrared image features to carry out feature testing, and outputting a prediction label; a multi-stage feature fusion module in the double-flow symmetric feature fusion network in which the attention mechanism is introduced is used for enhancing key information in visible light image features and infrared image features and performing multi-stage cascade average fusion on enhanced feature expressions to obtain a fusion result; and the identification module is used for identifying the fusion result